KEMAMPUAN ARTIFICIAL INTELLIGENCE TERHADAP PENDETEKSIAN FRAUD: STUDI LITERATUR

DOI:

https://doi.org/10.29303/akurasi.v7i1.488

Authors

  • Ervian Ridho Mawlidy Universitas Airlangga
  • Rieswandha Dio a:1:{s:5:"en_US";s:21:"Universitas Airlangga";}
  • Like Lorensa Universitas Airlangga

Keywords:

Artificial Intelligence, Financial Fraud, Audit, Audit Methdology, Digitalization Era

Abstract

This research aims to determine the role of artificial intelligence in detecting financial fraud in audits. The study was conducted by collecting 16 articles from reputable journals published between 2018-2024, which will be classified based on the methods used and the research results. The method used in this research is Systematic Literature Review (SLR), which is used to examine the results, methodologies, topics/themes, recommendations, and limitations of the published articles. The analysis results provide evidence that Artificial Intelligence (AI) has a positive impact on detecting financial fraud in audits. The forms of AI that have been implemented in companies are Artificial Neural Network (ANN) and Machine Learning. ANN is a model of a neural system inspired by human thinking processes. The use of ANN in detecting financial fraud can make a significant contribution to fraud prevention and detection efforts. Machine Learning is a technology capable of recognizing unusual patterns or anomalies that may indicate the possibility of fraud or manipulation in financial reports. Despite its potential benefits, the implementation of AI in audits is not without challenges. Privacy issues, data security, and ethical considerations surrounding the use of sensitive information are important factors that need to be addressed. Digital transformation involves not only technological influences but also changes in culture, operations, and business models

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Published

2024-06-24

How to Cite

Mawlidy, E. R., Dio, R., & Lorensa, L. (2024). KEMAMPUAN ARTIFICIAL INTELLIGENCE TERHADAP PENDETEKSIAN FRAUD: STUDI LITERATUR. Akurasi : Jurnal Studi Akuntansi Dan Keuangan, 7(1), 89–104. https://doi.org/10.29303/akurasi.v7i1.488

Issue

Vol. 7 No. 1 (2024): Akurasi: Jurnal Studi Akuntansi dan Keuangan, June 2024

Section

Articles

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